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Data · dataset · 2026

A mixed integer genetic algorithm used in chem-bio defense applications

Listed in National Center for Atmospheric Research

There are many problems in security and defense that require a robust optimization technique, including those that involve the release of a chemical or biological contaminant.

Description

Our problem, in particular, is computing the parameters to be used in modeling atmospheric transport and dispersion given field sensor measurements of contaminant concentration. This paper discusses using a genetic algorithm for addressing this problem.

An example is given how a mixed integer genetic algorithm can be used in conjunction with field sensor data to invert a forward model to obtain the meteorological data and source information necessary for prediction of the subsequent concentration field. A new mixed integer genetic algorithm is described that is a state-of-the-art tool capable of optimizing a wide range of objective functions. Such an algorithm is used here for optimizing atmospheric stability, wind speed, wind direction, rainout, and source location.

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We demonstrate that the algorithm is successful at reconstructing these meteorological and source parameters despite moderate correlations between their effects on the sensor data.

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Provenance · 1 source records, 7 field assertions
SourceKeyLast seenRaw
National Center for Atmospheric Research20eb3c66-16e4-42cb-87fd-f4b3c59c9fb79 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].local:field:earth-environmentalmapping · data ucar educonnector:data_ucar_edu@1.0.0
concepts[field].local:field:ocean-atmosphericmapping · data ucar educonnector:data_ucar_edu@1.0.0
created_datesource · data ucar educonnector:data_ucar_edu@1.0.0
descriptionsource · data ucar educonnector:data_ucar_edu@1.0.0/notes
publication_datesource · data ucar educonnector:data_ucar_edu@1.0.0
titlesource · data ucar educonnector:data_ucar_edu@1.0.0/title
updated_datesource · data ucar educonnector:data_ucar_edu@1.0.0